Intelligent Adversary Risk Analysis: A Bioterrorism Risk Management Model (PREPRINT)
Abstract
The tragic events of 911 and the concerns about the potential for a terrorist or hostile state attack with weapons of mass destruction have led to an increased emphasis on risk analysis for homeland security. Uncertain hazards (natural and engineering) have been analyzed using Probabilistic Risk Analysis (PRA). Unlike uncertain hazards, terrorists and hostile states are intelligent adversaries who adapt their plans and actions to achieve their strategic objectives. The critical risk analysis question addressed in this paper is as follows: Are the standard PRA techniques for uncertain hazard techniques adequate and appropriate for intelligent adversaries? Our answer is an emphatic no. We will show that treating adversary decisions as uncertain hazards is inappropriate because it provides the wrong assessment of risks. Specifically, the paper compares uncertain hazard risk analysis with intelligent adversary risk analysis, describes the intelligent adversary risk analysis challenges, and uses a defender-attacker-defender decision analysis model to evaluate defender investments. The model includes defender decisions prior to an attack; attacker decisions during the attack; defender actions after an attack; and the uncertainties of attack implementation, detection, and consequences. In section 1, we describe the difference between natural hazards and intelligent adversaries and demonstrate, with a simple example, that standard PRA does not properly assess the risk of an intelligent adversary attack. In section 2, we describe a canonical model for resource allocation decision making for an intelligent adversary problem using an illustrative bioterrorism example with notional data. In section 3, we describe the illustrative analysis results obtained for the model and discuss the insights they provide for risk management. In section 4, we describe the benefits and limitations of the model. Finally, we discuss future work and our conclusions.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 20, 2009
- Accession Number
- ADA522594
Entities
People
- Christopher M. Smith
- Frederick I. Moxley
- Gregory S. Parnell
Organizations
- United States Military Academy